assist (version 3.1.9)

predict.slm: Predict Method for Semiparametric Linear Mixed Effects Model Fits

Description

Predicted Values on different levels of random effects with the spline fit as part of fixed effects

Usage

# S3 method for slm
predict(object, newdata=NULL, ...)

Value

returned is a data.frame with columns given by the predictions at different levels and the grouping factors. Note that the smooth part of the spline fit is regarded as fixed.

Arguments

object

an object inheriting from class slm, representing a semi-parametric linear mixed effects model fit.

newdata

a data frame containing the values at which predictions are required. Only those predictors, referred to in the right side of the formula in the object, need to be present by name in newdata. Default is NULL, where predictions are made at the same values used to compute the object.

...

other arguments, but currently unused.

Author

Chunlei Ke and Yuedong Wang .

References

Wang, Y. (1998) Mixed Effects Smoothing Spline ANOVA. JRSS, Series B, 60:159--174.

Pinherio, J. C. and Bates, D. M. (2000) Mixed-effects Models in S and S-Plus. Springer.

See Also

slm

Examples

if (FALSE) {
data(dog)

dog.fit<-slm(y~group*time, rk=list(cubic(time), shrink1(group),
    rk.prod(kron(time-0.5),shrink1(group)),rk.prod(cubic(time), 
    shrink1(group))), random=list(dog=~1), data=dog)

predict(dog.fit)
}